FPGA Implementation of Pseudo-Random Number Generator for SRAM PUFs
LI Bing1, ZHOU Cen-jun1, CHEN Shuai1, JI Jian-hua2
1. School of Microelectronics, Southeast University, Nanjing, Jiangsu 210000, China;
2. School of Information Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China
Abstract:The problem of information security is becoming serious,and the random numbers are the cornerstone of information security systems.This paper proposes a Hash-based pseudo-random number generator (PRNG) which takes static random access memory physical unclonable functions (SRAM PUFs) as entropy sources.This PRNG verifies the availability of entropy sources online and reseeds dynamically which improved the security of pseudo-random numbers.Therefore,it can be securely applied in high-level secure cryptographic protocols.This PRNG is implemented on FPGA development platform and the generation speed is up to 598.1Mbps.Experimental results of the NIST statistical test suite show that,the pseudo-random numbers generated by this PRNG pass all random tests and have good randomness.
[1] Van Herrewege A.Lightweight PUF-Based Key and Random Number Generation[M].Belgian:KU Leuven,2015.19-26.
[2] Tsoi K H,Leung K H,Leong P H W.Compact FPGA-based true and pseudo random number generators[A].Arnold J.Proceedings of Field-Programmable Custom Computing Machines[C].New York:IEEE Computer Society,2003.51.
[3] Wachsmann C,Sadeghi A.Physically unclonable functions (PUFs):applications,models,and future directions[J].Synthesis Lectures on Information Security Privacy & Trust,2014,9(1):1-91.
[4] Holcomb D E,Burleson W P,Fu K.Power-up SRAM state as an identifying fingerprint and source of true random numbers[J].IEEE Transactions on Computers,2009,58(9):1198-1210.
[5] Cerda J C,Martinez C D,Comer J M,et al.An efficient FPGA random number generator using LFSRs and cellular automata[A].Rafla N.International Midwest Symposium on Circuits and Systems[C].New York:IEEE,2012.912-915.
[6] Leest V V D,Sluis E V D,Schrijen G J,et al.Efficient implementation of true random number generator based on SRAM PUFs[J].Cryptography and Security,2012,6805:300-318.
[7] Li D,Lu Z,Zou X,et al.PUFKEY:A high-security and high-throughput hardware true random number generator for sensor networks[J].Sensors,2015,15(10):26251-26266.
[8] Herder C,Yu M D,Koushanfar F,et al.Physical unclonable functions and applications:a tutorial[J].Proceedings of the IEEE,2014,102(8):1126-1141.
[9] Fd C C,Skorobogatov S.Low Temperature Data Remanence in Static RAM[R].Cambridge:University of Cambridge Computer Laboratory,2002.
[10] Barker E B,Kelsey J M.SP 800-90A.Recommendation for Random Number Generation Using Deterministic Random Bit Generators[M].USA:National Institute of Standards & Technology,2012.11-42.
[11] Kelsey J,Schneier B,Ferguson N.Yarrow-160:notes on the design and analysis of the Yarrow cryptographic pseudorandom number generator[A].Heys H.International Workshop on Selected Areas in Cryptography[C].Berlin:Springer-Verlag,1999.13-33.
[12] Kelsey J,Schneier B,Wagner D,et al.Cryptanalytic attacks on pseudorandom number generators[J].Lecture Notes in Computer Science,2000,1372:168-188.
[13] Kocher P C.Timing attacks on implementations of Diffie-Hellman,RSA,DSS,and other systems[A].Koblitz N.Advances in Cryptology[C].Berlin:Springer-Verlag,2001.104-113.
[14] Kocher P C,Jaffe J,Jun B.Differential power analysis[A].Wiener M.Advances in Cryptology[C].Berlin:Springer-Verlag,1999.388-397.
[15] Nedospasov D,Seifert J P,Helfmeier C,et al.Invasive PUF analysis[A].Fischer W.Fault Diagnosis and Tolerance in Cryptography[C].New York:IEEE Computer Society,2013.30-38.
[16] Helfmeier C,Boit C,Nedospasov D,et al.Cloning physically unclonable functions[A].Karri R.Hardware-Oriented Security and Trust[C].New York:IEEE,2013.1-6.
[17] Oren Y,Sadeghi A R,Wachsmann C.On the effectiveness of the remanence decay side-channel to clone memory-based PUFs[A].Bertoni G.Cryptographic Hardware and Embedded Systems[C].Berlin:Springer-Verlag,2013.107-125.
[18] Rukhin A,Soto J,Nechvatal J,et al.SP 800-22.A Statistical Test Suite for the Validation of Random Number Generators and Pseudo Random Number Generators for Cryptographic Applications[M].USA:National Institute of Standards & Technology,2010.1-79.